使用叫用模型API在 Amazon Bedrock 上叫用 Cohere 命令 - AWS SDK 程式碼範例

文件 AWS SDK AWS 範例 SDK 儲存庫中有更多可用的 GitHub 範例。

本文為英文版的機器翻譯版本,如內容有任何歧義或不一致之處,概以英文版為準。

使用叫用模型API在 Amazon Bedrock 上叫用 Cohere 命令

下列程式碼範例示範如何使用調用模型 API 將文字訊息傳送至 Cohere Command。

.NET
AWS SDK for .NET
注意

還有更多 on GitHub。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫中設定和執行。

使用調用模型 API 傳送文字訊息。

// Use the native inference API to send a text message to Cohere Command. using System; using System.IO; using System.Text.Json; using System.Text.Json.Nodes; using Amazon; using Amazon.BedrockRuntime; using Amazon.BedrockRuntime.Model; // Create a Bedrock Runtime client in the AWS Region you want to use. var client = new AmazonBedrockRuntimeClient(RegionEndpoint.USEast1); // Set the model ID, e.g., Command Light. var modelId = "cohere.command-light-text-v14"; // Define the user message. var userMessage = "Describe the purpose of a 'hello world' program in one line."; //Format the request payload using the model's native structure. var nativeRequest = JsonSerializer.Serialize(new { prompt = userMessage, max_tokens = 512, temperature = 0.5 }); // Create a request with the model ID and the model's native request payload. var request = new InvokeModelRequest() { ModelId = modelId, Body = new MemoryStream(System.Text.Encoding.UTF8.GetBytes(nativeRequest)), ContentType = "application/json" }; try { // Send the request to the Bedrock Runtime and wait for the response. var response = await client.InvokeModelAsync(request); // Decode the response body. var modelResponse = await JsonNode.ParseAsync(response.Body); // Extract and print the response text. var responseText = modelResponse["generations"]?[0]?["text"] ?? ""; Console.WriteLine(responseText); } catch (AmazonBedrockRuntimeException e) { Console.WriteLine($"ERROR: Can't invoke '{modelId}'. Reason: {e.Message}"); throw; }
  • 如需 API 詳細資訊,請參閱 InvokeModel AWS SDK for .NET 參考中的 API

Java
Java 2.x 的 SDK
注意

還有更多 on GitHub。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫中設定和執行。

使用調用模型 API 傳送文字訊息。

// Use the native inference API to send a text message to Cohere Command. import org.json.JSONObject; import org.json.JSONPointer; import software.amazon.awssdk.auth.credentials.DefaultCredentialsProvider; import software.amazon.awssdk.core.SdkBytes; import software.amazon.awssdk.core.exception.SdkClientException; import software.amazon.awssdk.regions.Region; import software.amazon.awssdk.services.bedrockruntime.BedrockRuntimeClient; public class Command_InvokeModel { public static String invokeModel() { // Create a Bedrock Runtime client in the AWS Region you want to use. // Replace the DefaultCredentialsProvider with your preferred credentials provider. var client = BedrockRuntimeClient.builder() .credentialsProvider(DefaultCredentialsProvider.create()) .region(Region.US_EAST_1) .build(); // Set the model ID, e.g., Command Light. var modelId = "cohere.command-light-text-v14"; // The InvokeModel API uses the model's native payload. // Learn more about the available inference parameters and response fields at: // https://docs.aws.amazon.com/bedrock/latest/userguide/model-parameters-cohere-command.html var nativeRequestTemplate = "{ \"prompt\": \"{{prompt}}\" }"; // Define the prompt for the model. var prompt = "Describe the purpose of a 'hello world' program in one line."; // Embed the prompt in the model's native request payload. String nativeRequest = nativeRequestTemplate.replace("{{prompt}}", prompt); try { // Encode and send the request to the Bedrock Runtime. var response = client.invokeModel(request -> request .body(SdkBytes.fromUtf8String(nativeRequest)) .modelId(modelId) ); // Decode the response body. var responseBody = new JSONObject(response.body().asUtf8String()); // Retrieve the generated text from the model's response. var text = new JSONPointer("/generations/0/text").queryFrom(responseBody).toString(); System.out.println(text); return text; } catch (SdkClientException e) { System.err.printf("ERROR: Can't invoke '%s'. Reason: %s", modelId, e.getMessage()); throw new RuntimeException(e); } } public static void main(String[] args) { invokeModel(); } }
  • 如需 API 詳細資訊,請參閱 InvokeModel AWS SDK for Java 2.x 參考中的 API

Python
SDK for Python (Boto3)
注意

還有更多 on GitHub。尋找完整範例,並了解如何在 AWS 程式碼範例儲存庫中設定和執行。

使用調用模型 API 傳送文字訊息。

# Use the native inference API to send a text message to Cohere Command. import boto3 import json from botocore.exceptions import ClientError # Create a Bedrock Runtime client in the AWS Region of your choice. client = boto3.client("bedrock-runtime", region_name="us-east-1") # Set the model ID, e.g., Command Light. model_id = "cohere.command-light-text-v14" # Define the prompt for the model. prompt = "Describe the purpose of a 'hello world' program in one line." # Format the request payload using the model's native structure. native_request = { "prompt": prompt, "max_tokens": 512, "temperature": 0.5, } # Convert the native request to JSON. request = json.dumps(native_request) try: # Invoke the model with the request. response = client.invoke_model(modelId=model_id, body=request) except (ClientError, Exception) as e: print(f"ERROR: Can't invoke '{model_id}'. Reason: {e}") exit(1) # Decode the response body. model_response = json.loads(response["body"].read()) # Extract and print the response text. response_text = model_response["generations"][0]["text"] print(response_text)
  • 如需 API 詳細資訊,請參閱 InvokeModel AWS SDK for Python (Boto3) Word 參考中的 API